Image registration is the process of transforming different sets of data into one coordinate system. Data can be multiple photographs, from different sensors, from different times, or from different viewpoints. Image registration is used in computer vision, medical imaging, military automatic target recognition, and compiling and analyzing images and data from satellites. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements.
Image registration involves combining two or more images, or selected points from the images, to produce a composite image containing data from each of the registered images. Real time registration of two video images from different cameras in dynamic conditions requires significant processing when such processing is done using only video data. In addition, video data is subject to blurring during fast changes in direction. This motion results in abrupt jumps or lags in final composite image. Normally the problem is solved by using image processing to register the images. Use of only image processing is compute intensive and can result in false registration.
Image processing methods commonly use 20 (Two Dimensional) convolution (x and y) or 3D (Three Dimensional) convolution (x, y, and roll). Also such methods use a direct calculation or involve a Fast Fourier Transform (FFT).
U.S Patent No: US 20120155785 A1 issued to Banner et al discloses a method of reducing blurring in an image of size greater than M columns by N rows of pixels, comprises deriving a blur kernel k representing the blur in the image, and deriving an inverse blur kernel k−1. The two dimensional matrix is convolved with the image over the whole image in the image pixel domain to produce an image with reduced blur. The method may be applied to a video sequence allowing the sequence of images to be deblurred in real time.
U.S Patent No: US 20090046160 A1 issued to Hayashi et al discloses methods for realizing a video blur detecting function include methods of detecting a video blur by means of a sensor such as an angular velocity sensor and methods of detecting it by means of a sensor and motion prediction of moving picture encoding.
The prior art processing methods are intensive. In addition they are subjected to blurring especially when the camera motion is fast. As a result there can be sudden jumps in image alignment during motion. In cases where the images have limited features, use of only image, processing can result in false registration. A need, therefore, exists for a way to reduce processing load and improve tracking.